Machine learning is a branch in computer science that studies the design of algorithms that can learn. Typical machine learning tasks are concept learning, function learning or “predictive modeling”, clustering and finding predictive patterns. These tasks are learned through available data that were observed through experiences or instructions, for example. Machine learning hopes that including the experience into its tasks will eventually improve the learning. The ultimate goal is to improve the learning in such a way that it becomes automatic, so that humans like ourselves don't need to interfere any more.
Code: NES_SK_2255
Duration: 60 Hrs / 6 Weeks / Customized
Mode: Online / Offline / Onsite
Module 1 - R Programming Fundamentals
Module 2 - Introduction to Applied Machine Learning
Module 3 - Machine Learning with R
Module 4 - Introduction to Applied Machine Learning
Module 5 - Supervised Machine Learning Models
Module 6 - Un-Supervised Machine Learning Models
Module 7 - Resampling Machine Learning Models
Introduction to Deep Learning
Practicals
Target Audience
Training Customization